Downloads · 30 days
109
9% of all-time downloads
Edentns_-_DataVortexS-10.7B-dpo-v1.2-gguf
RichardErkhov/Edentns_-_DataVortexS-10.7B-dpo-v1.2-gguf
Edentns_-_DataVortexS-10.7B-dpo-v1.2-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
All-time downloads
1.2K
Public
Repo size
122 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.gguf141 GB · 100%
At a glance
- Access
- Public
- Created
- Jul 29, 2024
- Updated
- Jul 30, 2024
- SHA
- 70718a22
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
DataVortexS-10.7B-dpo-v1.2 - GGUF
- Model creator: https://huggingface.co/Edentns/
- Original model: https://huggingface.co/Edentns/DataVortexS-10.7B-dpo-v1.2/
Original model description:
tags: - text-generation license: cc-by-nc-sa-4.0 language: - ko base_model: megastudy/M-SOLAR-10.7B-v1.3 pipeline_tag: text-generation
DataVortexS-10.7B-dpo-v1.2
<img src="./DataVortex.png" alt="DataVortex" style="height: 8em;">Our Team
| Research & Engineering | Product Management |
|---|---|
| Kwangseok Yang | Seunghyun Choi |
| Jeongwon Choi | Hyoseok Choi |
Model Details
Base Model
Trained On
- OS: Ubuntu 22.04
- GPU: H100 80GB 4ea
- transformers: v4.36.2
Instruction format
It follows Alpaca (Chat) format.
E.g.
text = """\
### System:
당신은 사람들이 정보를 찾을 수 있도록 도와주는 인공지능 비서입니다.
### User:
대한민국의 수도는 어디야?
### Assistant:
대한민국의 수도는 서울입니다.
### User:
서울 인구는 총 몇 명이야?
"""
Model Benchmark
Ko LM Eval Harness
| Task | 0-shot | 5-shot | 10-shot | 50-shot |
|---|---|---|---|---|
| kobest_boolq | 0.86665 | 0.932254 | 0.940132 | 0.941561 |
| kobest_copa | 0.723415 | 0.780594 | 0.778814 | 0.79982 |
| kobest_hellaswag | 0.471639 | 0.466883 | 0.472548 | 0.488648 |
| kobest_sentineg | 0.78514 | 0.964734 | 0.972281 | 0.972289 |
| Average | 0.711711 | 0.786116 | 0.790944 | 0.80058 |
Ko-LLM-Leaderboard
| Average | Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 |
|---|---|---|---|---|---|
| 56.53 | 52.73 | 64.83 | 52.99 | 58.36 | 53.72 |
Implementation Code
This model contains the chat_template instruction format.
You can use the code below.
from transformers import AutoModelForCausalLM, AutoTokenizer
device = "cuda" # the device to load the model onto
model = AutoModelForCausalLM.from_pretrained("Edentns/DataVortexS-10.7B-dpo-v1.2")
tokenizer = AutoTokenizer.from_pretrained("Edentns/DataVortexS-10.7B-dpo-v1.2")
messages = [
{"role": "system", "content": "당신은 사람들이 정보를 찾을 수 있도록 도와주는 인공지능 비서입니다."},
{"role": "user", "content": "대한민국의 수도는 어디야?"},
{"role": "assistant", "content": "대한민국의 수도는 서울입니다."},
{"role": "user", "content": "서울 인구는 총 몇 명이야?"}
]
encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")
model_inputs = encodeds.to(device)
model.to(device)
generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
decoded = tokenizer.batch_decode(generated_ids)
print(decoded[0])
License
The model is licensed under the cc-by-nc-sa-4.0 license, which allows others to copy, modify, and share the work non-commercially, as long as they give appropriate credit and distribute any derivative works under the same license.
<div align="center"> <a href="https://edentns.com/"> <img src="./Logo.png" alt="Logo" style="height: 3em;"> </a> </div>- Created
- Jul 29, 2024
- Updated
- Jul 30, 2024